The Multi-scale Aggregation Group (MSAG) is the most basic and important module of MDRN.
According to Figure REF , we can observe that MSAG is composed of a \(1 \times 1\)  fusion layer and \(N\)  MSABs, which is a simple but efficient feature extraction module.
Meanwhile, we also apply a long skip connection for global residual learning like [1]}.
This strategy can increase the information flow and solve the gradient disappearance problem.
